I am evaluating the impact of a project with NON-RANDOMIZED multiple interventions (3 treatment groups and 1 control/comparison group). I have a household survey data for two periods (baseline and follow-up).
To deal with selection bias (in particular), I am considering the use of Stata's teffects ipwra to obtain the average treatment effects.
I want to know from the experts in impact evaluation which estimation procedure is most appropriate.. and also if teffects ipwra does the same job as diff-in-diff regression with inverse probability weighting based on GPS?
Thank you
Related Posts with teffects ipwra and diff-in-diff with inverse probability weighting
Get the row number of a cellHi everyone, Suppose a variable y, with 100 obs, ranked by id (1 to 100). And among these obs, only…
Changing values of two variables within one (parallel) loopDear Stata Users, as mentioned in the thread title I got a question regarding parallel looping in S…
Reading in 10GB .csv dataset with not enough memory on my machineHello everyone, I need help reading in a 10GB .csv dataset with very limited physical memory on my c…
Why when I control for a key variable results do not change?Dear Statalist, I am estimating the effect of parental separation on the amount of time a child spe…
Predicting Probabilities with Fixed Effects Ordered Logit ModelHello, I am looking at whether losing a partner effects an individual's political view. I have a pan…
Subscribe to:
Post Comments (Atom)
0 Response to teffects ipwra and diff-in-diff with inverse probability weighting
Post a Comment